Gujarat Technological UniversitySummer 2026 examination

GTU 3161610 Data Warehousing and Mining Summer 2026 Question Paper & PDF

B.E. · IT Engineering · Semester 6 · Subject code 3161610
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Total
70 marks
To pass
23 marks (33%)
Duration
2.5 Hours 10:30 AM – 1:00 PM
Questions
5 with internal choice
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Q.1

14 Marks
(a)
3 marks
Explain various types of metadata in data warehouse.
(b)
4 marks
Give the benefits of data warehousing.
(c)
7 marks
What is cuboid? Explain following OLAP Operations with examples.
1)drill down
2)roll up
3)slice
4)dice

Q.2

14 Marks
(a)
3 marks
Differentiate OLAP and OLTP
(b)
4 marks

What is data mining? What are the major challenges of mining huge amount of data?

(c)
7 marks
Draw and explain data warehouse architecture.
(c)
7 marks
Explain the various stage of KDD process.

Q.3

14 Marks
(a)
3 marks
Write importance of preprocessing in data mining.
(b)
4 marks
Explain different types of data on which mining can be performed.
(c)
7 marks
Explain various schema for multidimensional database.
(a)
3 marks
Give the importance of dimensionality reduction.
(b)
4 marks

What is normalization? Explain min-max normalization with suitable example.

(c)
7 marks

Explain data smoothing methods to divide given data into bins of size 3 by bin means, by bin medians and by bin boundaries. Consider the data: 10, 2, 19, 18, 20, 18, 25, 28, 22

Q.4

14 Marks
(a)
3 marks
Differentiate Fact table vs. Dimension table.
(b)
4 marks
Explain support and confidence with example.
(c)
7 marks

Find frequent item-sets and association rules using Apriori algorithm on the following data set with minimum support count is 2 and minimum confidence is 75%. Sr. No TID List of items 1 T1 A,B,E 2 T2 B,D 3 T3 B,C 4 T4 A,B,D 5 T5 A,C 6 T6 B,C 7 T7 A,C 8 T8 A,B,C,E 9 T9 A,B,C

(a)
3 marks
Differentiate supervised and unsupervised learning.
(b)
4 marks
Explain various issues of classification.
(c)
7 marks
Explain Information Gain, Gain Ratio, Gini Index

Q.5

14 Marks
(a)
3 marks
Give differences between linear and logistic regression.
(b)
4 marks
What is outlier? Discuss different methods for outlier detection.
(c)
7 marks
Explain k-means clustering algorithm.
(a)
3 marks
Give the differences between Spatial and Temporal Data Mining.
(b)
4 marks
Write short note on text mining.
(c)
7 marks

What is web mining? Explain types of web mining. ---------------------- .

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About this paper

Official Gujarat Technological University (GTU) examination paper for Data Warehousing and Mining (Summer 2026, B.E. · IT Engineering, Sem 6). Features complete 70-mark regular & remedial examination pattern, official marking distribution across all 5 questions, and direct 1-click official PDF download.

Transcribed for student exam preparation from Gujarat Technological University official examination archives. Questions, syllabus guidelines, and curriculum marking schemes remain the intellectual property of Gujarat Technological University.

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